Search results

The construction industry has arrived at a crossroads of rapid technological progress. While it is foreseen that the advent of new construction technologies will disrupt the construction industry’s future, such disruptions often create the ideal environment for innovation. As poor payment practices continue to plague the construction industry, the advent of smart contracts has created an opportunity to rectify the inherent flaws in the mitigation of payment problems in traditional construction contracts. Given the intrinsic resistance of construction firms to such revolutionary changes, this study aims to understand the various factors influencing the adoption of smart contracts in the Singapore construction industry.

A mixed method was adopted involving quantifying respondents’ perceptions of the factors influencing smart contract adoption, and validation from a group of interviewees on the matter. Out of 461 registered quantity surveyor members contacted via the Singapore institute of surveyors and valuers website, 55 respondents took part in the survey. This is followed by semi-structured interviews to validate the survey results.

The findings indicate that construction firms have neither a significant knowledge of nor willingness to adopt smart contracts. A total of 29 institutional factors were also identified that significantly influence the adoption of smart contracts. The quantitative findings were further reinforced by qualitative interviews with five industry experts.

With recognition of and the successful formulation of the significant institutional drivers and barriers, the key findings of this study will be integral in driving the commercial adoption of smart contracts within the construction industry.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

This study aims to introduce and evaluate the COPULA framework, a construction project monitoring solution based on blockchain designed to address the inherent challenges of construction project monitoring and management. This research aims to enhance efficiency, transparency and trust within the dynamic and collaborative environment of the construction industry by leveraging the decentralized, secure and immutable nature of blockchain technology.

This paper employs a comprehensive approach encompassing the formulation of the COPULA model, the development of a digital solution using the ethereum blockchain and extensive testing to assess performance in terms of execution cost, time, integrity, immutability and security. A case analysis is conducted to demonstrate the practical application and benefits of blockchain technology in real-world construction project monitoring scenarios.

The findings reveal that the COPULA framework effectively addresses critical issues such as centralization, privacy and security vulnerabilities in construction project management. It facilitates seamless data exchange among stakeholders, ensuring real-time transparency and the creation of a tamper-proof communication channel. The framework demonstrates the potential to significantly enhance project efficiency and foster trust among all parties involved.

While the study provides promising insights into the application of blockchain technology in construction project monitoring, future research could explore the integration of COPULA with existing project management methodologies to broaden its applicability and impact. Further investigations into the solution’s scalability and adaptation to various construction project types and sizes are also suggested.

This research offers a comprehensive blockchain solution specifically tailored for the construction industry. Unlike prior studies focusing on theoretical aspects, this paper presents a practical, end-to-end solution encompassing model formulation, digital implementation, proof-of-concept testing and validation analysis. The COPULA framework marks a significant advancement in the digital transformation of construction project monitoring, providing a novel approach to overcoming longstanding industry challenges.

The exact process of construction projects performance assessment and benchmarking still remains subjective relying on qualitative techniques, which does not allow stakeholders to address the issues and the drawbacks of their respective projects as effectively as possible for performance improvement purposes. Hence, this research aims to establish a unified project performance score (PPS) for assessing and comparing projects performance.

Data were collected from Construction Industry Institute (CII) members and through University of Wisconsin active research projects. Exploratory data analysis was done to investigate the calculated performance metrics and the collected data characteristics. Data were converted into six performance metrics which were used as the independent variables in creating the PPS model. Logistic regression model was developed to generate the unified PPS equation in order to explain the variables that significantly affect construction projects successful post-completion performance. The PPS model was then applied on the collected dataset to benchmark projects in terms of project delivery systems, compensation types and project types in order to showcase the PPS capabilities and possible applications.

The model revealed that construction cost and schedule growth are the most important metrics in assessing projects performance, while RFIs’ processing time and change orders per million dollars were the features with the least effect on the PPS value. The authors found that integrated project delivery (IPD) and target value (TV) projects outperformed all other project delivery and compensation types. While, industrial projects showed the worst performance, as compared to commercial or institutional projects.

The PPS model can be used to assess the performance of any pool of executed projects, and introducing a novel addition to the field of construction business analytics which is a supplementary tool to successful decision making and performance improvement. Additionally, the bidding selection system can be revolutionized from a cost-based to a performance based one using the PPS model to improve the outcomes of the buyout process.

To increase university–industry collaboration and research commercialisation, the Australian government recently introduced the Intellectual Property (IP) Framework, a set of online standard contracts. This follows a predecessor standard contract initiative, the IP Toolkit, which has not previously been evaluated. This paper aims to examine standard contracting in the innovation sector, tracing the policymaking behind the IP Toolkit using the lens of Macneil’s relational contract theory, to assess prospects of success for the new IP Framework, and similar initiatives in other jurisdictions.

This is a disciplined-configurative case study, drawing on qualitative secondary data analysis and applying Macneil’s relational contracting theory to guide case construction and generate hypotheses around likely success of standard contracting initiatives (stakeholder sentiment, stakeholder adoption). Within-case analysis process-traces development of the IP Toolkit, to discover what the policymakers wanted, knew and computed – and to detail observable implications Macneil’s theory predicts. Its themes are triangulated with multiple sources.

The case study, via Macneil’s theory, confirms the first hypothesis (resistant stakeholder sentiment) and partly validates the second hypothesis (low levels of adoption), demonstrating limited suitability of standard contracting in the dynamic and highly uncertain space of university–industry collaboration.

The study provides insights into the limited role that standard contracts can play in improving national collaborative research and development performance.

This is a novel theory-driven case study triangulated with previously unpublished data on the IP Toolkit’s website usage, and data from recent consultations on the new IP Framework. It has broader implications for other jurisdictions considering adoption of the standard contract model.

This study examines how project uncertainties (environmental uncertainty and participant uncertainty) affect guanxi and contractual governance and assesses the mediating role of guanxi governance between project uncertainty and contractual governance.

Data were collected in two stages from Chinese contractors. First, in-depth interviews were conducted with nine construction engineering project practitioners in different contracts as a pilot for questionnaire designing. Second, a cross-sectional questionnaire survey was conducted with professionals and practitioners of construction enterprises to collect primary data. Partial least squares structural equation modeling (PLS-SEM) was used to test seven hypotheses based on data collected from 198 respondents.

Project environmental uncertainty promotes the use of guanxi governance, while project participant uncertainty hinders it; the relationship between both types of uncertainty and contractual governance is the same as with guanxi governance. Furthermore, guanxi governance promotes contractual governance and partially mediates project environmental uncertainty and contractual governance and a complete mediating role between project participant uncertainty and contractual governance.

As the interviewed samples are mainly from China, the study should be replicated using large representative samples from East Asian countries, such as Japan and South Korea, to gain a more comprehensive understanding of the influence of guanxi governance. Further, while the internal consistency reliability and convergent validity of the questionnaire data in this study align with the standards, a larger sample size would improve the reliability and validity of the research results and better represent the overall work situation of contractors, owners and public policymakers.

The results provide insights into project governance research and have implications for construction practitioners in deploying governance-related resources.

The construction industry has struggled to deliver schemes on time to budget and right-first-time (RFT). There have been many studies into nonconformance and rework through quantitative research over the years to understand why the industry continues to see similar issues of failure. Some scholars have reported rework figures as high as 12.6% of total contract value, highlighting major concerns of the sustainability of construction projects. Separately, however, there have been few studies that explore and detail the views of industry professions who are caught in the middle of quality issues, to understand their perceptions of where the industry is failing. As such, this paper interrogates qualitative data (open-ended questions) on the topic of nonconformance and rework in construction to understand what industry professionals believe are the causes and suggested improvement areas.

A qualitative approach is adopted for this research. An industry survey consisting of seven open-ended questions is presented to two professional working groups within a Tier 1 contractor, and outputs are analysed using statistic software (NVivo 12) to identify prominent themes for discussion. Inductive analysis is undertaken to gain further insight into responses to yield recurrent areas for continuous improvement.

Qualitative analysis of the survey reveals a persistent prioritisation of cost and programme over quality management in construction project. Furthermore, feedback from construction professionals present a number of improvement areas that must be addressed to improve quality. These include increased training and competency investment, overhauling quality behaviours, providing greater quality leadership direction and reshaping the way clients govern schemes.

There are limitations to this paper that require noting. Firstly, the survey was conducted within one principal contractor with varying levels of knowledge across multiple sectors. Secondly, the case study was from one major highways scheme; therefore, the generalisability of the findings is limited. It is suggested that a similar exercise is undertaken in other sectors to uncover similar improvement avenues.

The implications of this study calls for quality to be re-evaluated at project, company, sector and government levels to overhaul how quality is delivered. Furthermore, the paper identifies critical learning outcomes for the construction sector to take forward, including the need to reassess projects to ensure they are appropriately equip with competent personnel under a vetted, progressive training programme, share collaborative behaviours that value quality delivery on an equal standing to safety, programme and cost and tackle the inappropriate resource dilemmas projects finding themselves in through clear tendering and accurate planning. In addition, before making erratic decisions, projects must assess the risk profiling of proceed without approved design details and include the client in the decision-making process. Moreover, the findings call for a greater collaborative environment between the construction team and quality management department, rather than being seen as obstructive (i.e. compliance based policing). All of these must be driven by leadership to overhaul the way quality is managed on schemes. The findings demonstrate the importance and impact from open-ended survey response data studies to enhance quantitative outcomes and help provide strengthened proposals of improvement.

This paper addresses the highly sensitive area of quality failure outcomes and interrogates them via an industry survey within a major UK contractor for feedback. Unique insights are gained into how industry professionals perceive quality in construction. From previous research, this has been largely missing and offers a valuable addition in understanding the “quality status quo” from those delivering schemes.

This study examines whether green buildings enjoy more favorable financing terms compared to their non-green counterparts, exploring the presence of a green discount in commercial real estate lending. Despite the extensive research on green premiums on the equity side, lending has received limited attention in the existing literature, even as regulations have increased and ambitious net-zero targets have been set in the banking sector.

In this study, the authors leverage a unique dataset comprising European commercial loan data spanning from 2018 to 2023, with a total loan value exceeding €30 billion. Hedonic regression analysis is used to isolate a potential green discount. Specifically, the authors rely on property assessments conducted by lenders to investigate whether green properties exhibit lower interest rate spreads and higher loan-to-value (LTV) ratios.

The findings reveal the existence of a green discount in European commercial real estate lending, with green buildings enjoying a 5.35% lower contracted loan spread and a 3.92% lower target spread compared to their non-green counterparts. However, this analysis does not indicate any distinct advantage in terms of LTV ratios for green buildings.

This research contributes to a deeper understanding of the interaction between green properties and commercial real estate lending, offering valuable insights for both lenders and investors.

This study, to the best of the authors’ knowledge, represents the first of its kind in a European context and provides empirical evidence for the presence of a green discount.

The purpose of this study is to investigate the influences of the characteristics of procurement strategies, in this instance labour-only, on project performance concerning health and safety (H&S), a project performance indicator.

Using non-probability purposeful and snowballing sampling methods, questionnaires were used to collect data from construction professionals in Nigeria. This was then analysed using descriptive (frequency and mean scores) and inferential statistics (Mann–Whitney-U and Kendall's Tau_b tests).

The findings indicate a statistically significant negative correlation between ‘the level of client involvement and ‘fatalities' and a positive one with ‘conducting of health and safety risk assessment' and ‘conducting employee surveys on health and safety attitude’. Poor hygiene is found to be the worst lagging indicator, while conducting of inspection is the most adopted leading indicator of project health and safety performance. It also emerged that there is no significant difference in the health and safety performance of projects procured through the procurement strategy in urban and rural areas.

The study provides valuable insight into the complexities in H&S management due to the high level of client involvement in labour-only procurement system (LoPS) projects and the level of diversity in their responsibilities therein. It creates a fundamental direction for developing a detailed framework or guidance notes for client involvement in the integration of H&S into LoPS projects.

This is the first study that examines the influence of the characteristics of procurement strategy on project health and safety performance. Evidence in the literature shows that project delivery outcomes significantly improve if procurement is strategically used, including when it is considered early in projects. However, integrating H&S into procurement strategies has received little attention.

This paper aims to provide an integrated BIM-based approach for quantity take-off for progress payments in the context of high-rise buildings in Vietnam. It tries to find answers for the following questions: (1) When to start the QTO processes to facilitate the contract progress payments? (2) What information is required to measure the quantity of works to estimate contract progress payment (3) What are the challenges to manage (i.e. create, store, update and exploit)? What are the required information for this BIM use? and (4) How to process the information to deliver BIM-based QTO to facilitate contract progress payment?

The paper applied a deductive approach and expert consensus through a Delphi procedure to adapt to current innovation around BIM-based QTO. Starting with a literature review, it then discusses current practices in BIM-based QTO in general and high-rise building projects in particular. Challenges were compiled from the previous studies for references for BIM-based QTO to facilitate contract progress payment for high-rise building projects in Vietnam. A framework was developed considering a standard information management process throughout the construction lifecycle, when the BIM use of this study is delivered. The framework was validated with Delphi technique.

Four major challenges for BIM-based QTO discovered: new types of information required for the BIM model, changes and updates as projects progress, low interoperability between BIM model and estimation software, potentiality of low productivity and accuracy in data entry. Required information for QTO to facilitate progress payments in high-rise building projects include Object Geometric/Appearance Information, Structural Components' Definition and Contextual Information. Trade-offs between “Speed – Level of Detail–Applicable Breadth” and “Quality – Productivity” are proposed to consider the information amount to input at a time when creating/updating BIM objects. Interoperability check needed for creating, authoring/updating processing the BIM model's objects.

This paper is not flawless. The first limitation lies in that the theoretical framework was established only based on desk research and small number of expert judgment. Further primary data collection would be needed to determine exactly how the framework underlies widespread practices. Secondly, this study only discussed the quantity take-off specifically for contract progress payment, but not for other purposes or broader BIM uses. Further research in this field would be of great help in developing a standard protocol for automatic quantity surveying system in Vietnam.

A new theoretical framework for BIM-based QTO validated with Delphi technique to facilitate progress payments for high-rise building projects, considering all information management stages and the phases of information development in the project lifecycle. The framework identified four types of information required for this QTO, detailed considerations for strategies (Library Objects Development, BIM Objects Information Declaration, BIM-based QTO) for better managing the information for this BIM use. Two trade-offs of “Speed – LOD–Applicable Breadth” and “Quality – Productivity” have been proposed for facilitating the strategies and also for enhancing the total efficiency and effectiveness of the QTO process.